go-doudou VS go

Github repo: https://github.com/unionj-cloud/go-doudou Latest release: v1.3.2

Update documentation to latest version https://go-doudou.github.io

If you like sqlx, I recommend you to have a look at go-doudou built-in lightweight orm based on sqlx. It can do struct to table and table to struct migration/sync, generate dao layer code to simplify your single table CRUD operations, and it also can print SQL query with parameters substituded along with opentracing compatible trace ID for locating problems, and it will have more features coming such as cache layer... Here is the repo: https://github.com/unionj-cloud/go-doudou

I recommend go-doudou for you: https://github.com/unionj-cloud/go-doudou Here is online documentation: https://go-doudou.github.io/

Please take a look at https://github.com/unionj-cloud/go-doudou This is a microservice framework written in Go. I opened it a year ago. It's production ready, but there are a lot of featues not implemented yet. I hope community can help me build it together.

Go-doudou released v1.0.3: https://github.com/unionj-cloud/go-doudou/releases/tag/v1.0.3 Add full support for Alibaba Nacos configuration management and Ctrip Apollo configuration management Documentation: https://go-doudou.github.io/guide/configuration.html

Hi gophers, go-doudou released v1.0.0 version today: https://github.com/unionj-cloud/go-doudou/releases/tag/v1.0.0. And I finished online documentation for go-doudou though there is only English version: https://go-doudou.github.io. I also uploaded a real-world word cloud application to github: https://github.com/unionj-cloud/go-doudou-tutorials/tree/master/wordcloud. You can use this project as scaffold to build your microservices.

In this tutorial, I will introduce go-doudou microservice framework to you. Go-doudou has built-in service register, discover and fault tolerance features based on gossip protocol, and it uses gorilla/mux as http router, and uses golang interface as IDL(Interface Definition Language). Go-doudou is an IDL compiler and server/client code generator tool at first, then it becomes a microservice framework. Its RESTful version is stable and production ready, while grpc version is in early development.

A Discussion about including this package in Go as encoding/json/v2 has been started on the Go Github project on 2023-10-05. Please provide your feedback there.

I like the Principles section. Very measured and practical approach to releasing new stdlib packages. https://go.dev/blog/randv2#principles

The end of the post they mention that an encoding/json/v2 package is in the works: https://github.com/golang/go/discussions/63397

There used to be the GO FIPS branch :

https://github.com/golang/go/tree/dev.boringcrypto/misc/bori...

But it looks dead.

And it looks like https://github.com/golang-fips/go as well.

I'm not sure what exactly you mean by acknowledgement, but here are some counterexamples:

- A proposal for sum types by a Go team member: https://github.com/golang/go/issues/57644

- The community proposal with some comments from the Go team: https://github.com/golang/go/issues/19412

Here are some excerpts from the latest Go survey [1]:

- "The top responses in the closed-form were learning how to write Go effectively (15%) and the verbosity of error handling (13%)."

- "The most common response mentioned Go’s type system, and often asked specifically for enums, option types, or sum types in Go."

I think the problem is not the lack of will on the part of the Go team, but rather that these issues are not easy to fix in a way that fits the language and doesn't cause too many issues with backwards compatibility.

[1]: https://go.dev/blog/survey2024-h1-results

Now, I’m not going to use C++ again; I left that chapter years ago, and it’s not going to happen. C++ isn’t memory safe and easy to use and would require extended time for developers to adapt. Rust is the new kid on the block, but I’ve heard mixed opinions about its developer experience, and there aren’t many libraries around it yet. LLRD is too new for my taste, but **Go** caught my attention.

Generative AI development has been democratised, thanks to powerful Machine Learning models (specifically Large Language Models such as Claude, Meta's LLama 2, etc.) being exposed by managed platforms/services as API calls. This frees developers from the infrastructure concerns and lets them focus on the core business problems. This also means that developers are free to use the programming language best suited for their solution. Python has typically been the go-to language when it comes to AI/ML solutions, but there is more flexibility in this area. In this post you will see how to leverage the Go programming language to use Vector Databases and techniques such as Retrieval Augmented Generation (RAG) with langchaingo. If you are a Go developer who wants to how to build learn generative AI applications, you are in the right place!

net/http: add methods and path variables to ServeMux patterns Discussion about ServeMux enhancements

Make sure you have Go installed https://go.dev/.